Takata Ryo, Katagiri Toyomasa, Kanehira Mitsugu, Shuin Taro, Miki Tsuneharu, Namiki Mikio, Kohri Kenjiro, Tsunoda Tatsuhiko, Fujioka Tomoaki, Nakamura Yusuke
Laboratory of Molecular Medicine, Human Genome Center, Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, Japan.
Cancer Sci. 2007 Jan;98(1):113-7. doi: 10.1111/j.1349-7006.2006.00366.x.
To predict the efficacy of the M-VAC neoadjuvant chemotherapy for invasive bladder cancers, we previously established the method to calculate the prediction score on the basis of expression profiles of 14 predictive genes. This scoring system had clearly distinguished the responder group from the non-responder group. To further validate the clinical significance of the system, we applied it to 22 additional cases of bladder cancer patients and found that the scoring system correctly predicted clinical response for 19 of the 22 test cases. The group of patients with positive predictive scores had significantly longer survival than that with negative scores. When we compared our results with a previous report describing the prognosis of the patients with cystectomy alone, the results imply that patients with positive scores are likely to benefit from M-VAC neoadjuvant chemotherapy, but that the chemotherapy would shorten the lives of patients with negative scores. We are confident that our prediction system to M-VAC therapy should provide opportunities for achieving better prognosis and improving the quality of life of patients. Taken together, our data suggest that the goal of 'personalized medicine', prescribing the appropriate treatment regimen for each patient, may be achievable by selecting specific sets of genes for their predictive values according to the approach shown here.
为预测M-VAC新辅助化疗对浸润性膀胱癌的疗效,我们此前建立了基于14个预测基因表达谱计算预测评分的方法。该评分系统能明确区分反应组和无反应组。为进一步验证该系统的临床意义,我们将其应用于另外22例膀胱癌患者,发现该评分系统正确预测了22例测试病例中19例的临床反应。预测评分阳性的患者组生存时间显著长于评分阴性的患者组。当我们将我们的结果与之前一篇描述单纯膀胱切除术患者预后的报告进行比较时,结果表明评分阳性的患者可能从M-VAC新辅助化疗中获益,但化疗会缩短评分阴性患者的生命。我们相信我们对M-VAC治疗的预测系统应为实现更好的预后和改善患者生活质量提供机会。综上所述,我们的数据表明,根据此处所示方法选择具有预测价值的特定基因集,“个性化医疗”(为每位患者制定合适的治疗方案)这一目标或许可以实现。